This workshop is an introduction to the new version 8.2 of GRASS GIS, showcasing the new functionality and the heavily redesigned graphical user interface. It also explores the interaction with data (visualization, styling, map elements), the analysis of data from different domains, and it introduces to automated processing.
We will introduce to Python 3 scripting, spatio-temporal data analysis, and more.
Candidate datasets: improved ERA5 land air temperature, surface temperature and precipitation (daily data).
Software requirements: GRASS GIS 8.2
GRASS GIS supports time-series processing for vector, raster, and volume data. This workshop offers a micro-introduction to Sentinel satellite data archives, and the various ways to access them. It also explores the i.sentinel toolset which allows querying Sentinel data coverage for a region of interest, downloading from multiple data sources, performing atmospheric and topographic corrections, and cloud/shadow masking. This workshop also gives a preparation of data for multitemporal analyses through automatic creation of a space-time raster dataset (strds), It explores the computation of NDVI time series. Eventually we run a simple RandomForest landuse classification on Sentinel-2 data.
Software requirements: We will run GRASS GIS 8.2 on Google Colab.
After a short introduction to geoprocessing services we will showcase OGC WPS with a focus on Request examples ("GetCapabilities", "DescribeProcess" and "Execute"). Then the OGC API - Processes Standard which supports the wrapping of computational tasks into executable processes is briefly explained.
In the second part we introduce actinia which is an open source REST API for scalable, distributed, high performance processing of geographical data.
Description will be updated soon! Please, revisit this page.
Software requirements: opengeohub/py-geo docker image (gdal, rasterio, geopandas, eumap).
LUCAS (Land Use and Coverage Area frame Survey) is an activity that performs repeated in-situ surveys over Europe every three years since 2006. The dataset is unique in many aspects, however, it is currently not available through a standardized interface, machine-to-machine. Moreover, the evolution of the surveys limits the change analysis with the dataset. Our goal was to develop an open-source system to fill these gaps.
Welcome session - Welcome to participants, Introduction of the GeoHarmonizer project, its scopes, goals and outcomes, Introduction of all partners involved.
Closing ceremony with training sessions and conferene evaluation. Overview and evaluation of the GeoHarmonizer project, farawell from all project partners